Triple

T9754019
Position Surface form Disambiguated ID Type / Status
Subject Mater E236509 entity
Predicate creator P184 FINISHED
Object Jorgen Klubien E827495 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Jorgen Klubien | Statement: [Mater, creator, Jorgen Klubien]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jorgen Klubien
Context triple: [Mater, creator, Jorgen Klubien]
  • A. Jorgen Klubien chosen
    Jorgen Klubien is a Danish storyboard artist, animator, and screenwriter known for his work on major animated films at studios like Disney and Pixar.
  • B. Klaus Lange
    Klaus Lange is a German politician who served as a member of the Bundestag representing the Social Democratic Party (SPD).
  • C. Joachim Lemelsen
    Joachim Lemelsen was a German Wehrmacht general during World War II who held several high-ranking field commands on the Eastern and Italian fronts.
  • D. Carl Kjeldsberg
    Carl Kjeldsberg is a pathologist and academic leader best known as a co-founder of ARUP Laboratories, a major national clinical and anatomic pathology reference laboratory.
  • E. Jürgen Marcussen
    Jürgen Marcussen was a Danish organ builder best known as the founder of the renowned pipe organ manufacturing firm Marcussen & Søn.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ca84d4eddc8190996fec1417d2bae8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9fb01ad08190b2435fa505c622bc completed April 1, 2026, 10:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69d20d048c5081908c891633129dc5d6 completed April 5, 2026, 7:19 a.m.
Created at: March 30, 2026, 8:24 p.m.